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首页> 外文会议>International Conference on Communication and Electronics Systems >Detection and Tracking of Anxiety Related Diseases for Autism Spectrum Disorder Using ECG
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Detection and Tracking of Anxiety Related Diseases for Autism Spectrum Disorder Using ECG

机译：使用ECG对自闭症谱系障碍的焦虑相关疾病进行检测和追踪

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摘要

Anxiety distress are excessive or continual panic of everyday circumstances causing behavioral and emotional consequences, eventually leading to diseases like heart attack, epilepsy and dyspnea. Anxiety disorders are common for people with developmental disorders like autism spectrum disorder, cerebral palsy, down syndrome. Patients suffering from these diseases have difficulties in communication and emotional recognition eventually leading to narrow interests and repetitive behavior. Sometimes their ways of communicating any symptoms may not be recognizable by the caretakers, hence building up a need of a non-invasive, continuous, real-time detection and tracking of their ECG signals for prediction of these diseases providing possible medications. Here a system framework based on unscented Kalman filter (UKF) is developed to continuously detect and track the R-R interval for anxiety prediction to make these unpredictable diseases predictable and reducing death tolls with timely treatment.
机译：焦虑困扰是对日常情况的过度或持续恐慌，导致行为和情感后果，最终导致心脏病，癫痫和呼吸困难等疾病。患有自闭症谱系障碍，脑瘫，唐氏综合症等发育障碍的人常见焦虑症。患有这些疾病的患者在沟通和情感识别方面存在困难，最终导致兴趣缩小和行为重复。有时，看护者可能无法识别他们传达任何症状的方式，因此需要无创，连续，实时检测和跟踪其ECG信号，以预测这些疾病并提供可能的药物。在这里，开发了基于无味卡尔曼滤波器（UKF）的系统框架，以连续检测和跟踪R-R间隔以进行焦虑预测，从而使这些不可预测的疾病可预测并通过及时治疗减少死亡人数。

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